Study On Key Technologies Of Intelligent Vehicles In ITS

Intelligent transport system (ITS) can increase transportation efficiency, decrease transportation cost and energy consumption, and improve vehicle's safety. ITS is the research direction of transportation. Intelligent vehicle (IV) is the core of ITS and the research direction of future automobile. Aiming at some key techniques of intelligent vehicle on the highway, the paper has some researches on state detection and environment perception, modeling, motion control algorithms, bottom control subsystems and global path planning and navigation.Due to some characteristics of vehicle's motion, such as nonlinear, strong coupling, time-variant parameters, it is very difficult to control vehicle's motion. The paper presents a new idea that with spatial compression dimension replacing temporal dimension, motion mode space of vehicle is established. Clustering technique is applied to establish the motion model space and sub-space, confirm the scope of vehicle motion, and model intelligent vehicle's motion mode space. The paper pioneers the research of vehicle's dynamics and has very important theoretical significance and practical worthiness.With noise addition, key parameters selection, reference path setting, and random initial state setting, we design the mode-based intelligent controller and provide a new design method PBICD for complex object's controller. We do some simulation for intelligent vehicle's motion controller designed by PBICD and do some experiments for ATRV mobile robot's motion controller. With simulation, we find the key parameters of vehicle and execution system which are important for IV's motion control performance. Especially, we make sure that the characteristics of brake is the key impact factor of motion control performance. The result provides some basis for the development of IV integration system. It has very important significance.Aiming at the IV's environment is a large network with many nodes and roads, Mapinfo is applied to develop the digital e-map. A local optimal A* heuristic searching algorithm is presented for global shortest path planning. Combining with Jinan city transportation, Mapinfo and Visual Basic 6.0 are used as simulation tools. The simulation results prove that the algorithm can search the shortest path quickly and decrease the searching time. We develop some application software, such as computer vision based roadway line identification, vehicle motion mode analysis, vehicle motion control, vehicle navigation and path planning with MATLAB or VB. This software provides tool for research on some related key techniques. With software integrating technique, black-box duplication, various software developed by MATALB or VB are integrated to realize"intelligent vehicle motion mode analysis and motion controller auto designing"software. The software provides an ideal development environment for research of intelligent vehicles.